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1.
In this paper, a constrained control scheme based on model reference adaptive control is investigated for the longitudinal motion of a commercial aircraft with actuator faults and saturation nonlinearities. Actuator faults and constraints are both important factors adversely affecting the stability and performance of flight control systems. An adaptive adjustment law based on Lyapunov function is utilized to adjust the fault-tolerant control law. Both additive and multiplicative faults are considered in the designed controller to deal with the three types of actuator faults: locked in place, loss of effectiveness, and bias. Moreover, different techniques are implemented in the basic and fault-tolerant controller to anti-windup. Proofs for the stability of the two modified controllers which improve the performance of control system operating in the presence of actuator faults and saturations are proposed. Finally, a numerical example of the anti-windup fault-tolerant controller for a commercial aircraft is demonstrated. The stability and performance improvements can be accrued with the presented fault-tolerant control scheme.  相似文献   

2.
This paper investigates the controller design problem of cyber-physical systems (CPSs) to ensure the reliability and security when actuator faults in physical layers and attacks in cyber layers occur simultaneously. The actuator faults are time-varying, which cover bias fault, outage, loss of effectiveness and stuck. Besides that, some state-dependent cyber attacks are launched in control input commands and system measurement data channels, which may lead state information to the opposite direction. A novel co-design controller scheme is constructed by adopting a new Lyapunov function, Nussbaum-type function, and direct adaptive technique, which may further relax the requirements of actuator/sensor attacks information. It is proven that the states of the closed-loop system asymptotically converge to zero even if actuator faults, actuator attacks and sensor attack are time-varying and co-existing. Finally, simulation results are presented to show the effectiveness of the proposed control method.  相似文献   

3.
This paper studies the adaptive tracking control problem for a class of uncertain high-order fully actuated (HOFA) systems with actuator faults and full-state constraints. Firstly, we design a novel nonlinear transformation function (NTF) only related to state and constraint boundaries and capable of handling asymmetric time-varying constraints. With the designed function, we obtain an equivalent totally unconstrained HOFA model which is generally simpler to design controllers than first-order state-space model. Then, the adaptive fault-tolerant controller is constructed with the help of the HOFA approach. By applying the Lyapunov stability theory, it is rigorously proved that the output tracking error converges to zero asymptotically, other signals of the resulting closed-loop systems are bounded, and full-state constraints are not violated for all time. Finally, the simulation results verify the efficiency of the proposed control design method.  相似文献   

4.
In this paper, a novel adaptive control is investigated for robotic manipulators to unify the study of predefined performance control, input saturation and dynamic uncertainties. The focus is to achieve three user-defined performance indices of the closed-loop system with simultaneous existence of input constraints and model uncertainties, that is overshoot, precision within prescribed finite time and predefined steady-state error. To ensure the performance constraints, an error transformation is constructed for the manipulators by two auxiliary functions and embedded into the barrier Lyapunov function (BLF) in the backstepping analysis. Furthermore, the adaptive control strategies and the adaptive anti-saturation compensator are, respectively, developed to address the dynamics uncertainties and the actuator saturation. The Lyapunov analysis is employed to show that all the closed-loop signals are bounded. Finally, simulation studies and experiments on Baxter robot demonstrate the effectiveness of the proposed method.  相似文献   

5.
Strap-down seeker is rigidly fixed onto the missile body, which results in detection information being coupled to the missile’s attitude and having a narrow field-of-view (FOV). During the terminal guidance flight, attitude adjustment of the missile may lose the target’s lock and reduce interception accuracy. Therefore, this paper investigates three-dimensional integrated guidance and control (IGC) under the constraints of the FOV and roll angle for skid-to-turn (STT) missile with strap-down seeker. A new low-order IGC model is constructed by establishing a second-order model of body line-of-sight (BLOS) angle based on strap-down decoupling theory and combining it with the second-order roll angle equation. Furthermore, a low-order fixed-time IGC scheme is developed using the integral barrier Lyapunov function (iBLF) to limit BLOS and roll angles. Fixed-time filter, which avoids the “complexity explosion” caused by conventional back-stepping technique, is utilized for obtaining virtual control command and its derivative. A fixed-time disturbance observer is introduced to compensate for the lumped disturbance. According to Lyapunov stability theory, it is proven that the proposed IGC scheme can make the closed-loop system converge within a fixed time. Finally, the effectiveness and robustness of the IGC scheme are verified by various numerical simulations.  相似文献   

6.
This paper investigates the adaptive fuzzy output feedback fault-tolerant tracking control problem for a class of switched uncertain nonlinear systems with unknown sensor faults. In this paper, since the sensor may suffer from an unknown constant loss scaling failure, only actual output can be used for feedback design. A failure factor is employed to represent the loss of effectiveness faults. Then, an adaptive estimation coefficient is introduced to estimate the failure factor, and a state observer based on the actual output is constructed to estimate the system states. Fuzzy logic systems are used to approximate the unknown nonlinear functions. Based on the Lyapunov function method and the backstepping technique, the proposed control scheme with average dwell time constraints can guarantee that all states of the closed-loop system are bounded and the tracking error can converge to a small neighborhood of zero. Finally, two simulation examples are given to illustrate the effectiveness of the proposed scheme.  相似文献   

7.
The present paper proposes two new schemes of sensor fault estimation for a class of nonlinear systems and investigates their performances by applying these to satellite control systems. Both of the schemes essentially transform the original system into two subsystems (subsystems 1 and 2), where subsystem-1 includes the effects of system uncertainties, but is free from sensor faults and subsystem-2 has sensor faults but without any uncertainties. Sensor faults in subsystem-2 are treated as actuator faults by using integral observer based approach. The effects of system uncertainties in subsystem-1 can be completely eliminated by a sliding mode observer (SMO). In the first scheme, the sensor faults present in subsystem-2 are estimated with arbitrary accuracy using a SMO. In the second scheme, the sensor faults are estimated by designing an adaptive observer (AO). The sufficient condition of stability of the proposed schemes has been derived and expressed as a linear matrix inequality (LMI) optimization problem and the design parameters of the observers are determined by using LMI techniques. The effectiveness of the schemes in estimating sensor faults is illustrated by considering an example of a satellite control system. The results of the simulation demonstrate that the proposed schemes can successfully estimate sensor faults even in the presence of system uncertainties.  相似文献   

8.
In this paper, a novel tracking control scheme for continuous-time nonlinear affine systems with actuator faults is proposed by using a policy iteration (PI) based adaptive control algorithm. According to the controlled system and desired reference trajectory, a novel augmented tracking system is constructed and the tracking control problem is converted to the stabilizing issue of the corresponding error dynamic system. PI algorithm, generally used in optimal control and intelligence technique fields, is an important reinforcement learning method to solve the performance function by critic neural network (NN) approximation, which satisfies the Lyapunov equation. For the augmented tracking error system with actuator faults, an online PI based fault-tolerant control law is proposed, where a new tuning law of the adaptive parameter is designed to tolerate four common kinds of actuator faults. The stability of the tracking error dynamic with actuator faults is guaranteed by using Lyapunov theory, and the tracking errors satisfy uniformly bounded as the adaptive parameters get converged. Finally, the designed fault-tolerant feedback control algorithm for nonlinear tracking system with actuator faults is applied in two cases to track the desired reference trajectory, and the simulation results demonstrate the effectiveness and applicability of the proposed method.  相似文献   

9.
In this paper, a learning-based active fault-tolerant control (FTC) scheme for robot manipulators with uncertainties and actuator faults is proposed. Unlike traditional FTC methods, with dynamic learning theory, both uncertainties and actuator faults can be accurately identified/learned by radial basis function networks. Based on the learned knowledge, dynamical classifiers and experience-based controllers corresponding to different fault modes are constructed. With the help of dynamical classifiers, fault detection and isolation can be obtained rapidly and accurately, and the correct experience-based controller (instead of the controller reconfigured online) corresponding to the current fault system is selected to compensate for faults, and superior control performance is achieved, even in the presence of faults. The simulation studies demonstrate the feasibility of the proposed FTC method.  相似文献   

10.
This paper investigates the finite-time cooperative formation control problem for a heterogeneous system consisting of an unmanned ground vehicle (UGV) - the leader and an unmanned aerial vehicle (UAV) - the follower. The UAV system under consideration is subject to modeling uncertainties, external disturbance as well as actuator faults simultaneously, which is associated with aerodynamic and gyroscopic effects, payload mass, and other external forces. First, a backstepping controller is developed to stabilize the leader system to track the desired trajectory. Second, a robust nonsingular fast terminal sliding mode surface is designed for UAV and finite-time position control is achieved using terminal sliding mode technique, which ensures the formation error converges to zero in finite time in the presence of actuator faults and other uncertainties. Furthermore, by combining the radial basis function neural networks (NNs) with adaptive virtual parameter technology, a novel NN-based adaptive nonsingular fast terminal sliding formation controller (NN-ANFTSMFC) is developed. By means of the proposed adaptive control strategy, both uncertainties and actuator faults can be compensated without the prior knowledges of the uncertainty bounds and fault information. By using the proposed control schemes, larger actuator faults can be tolerated while eliminating control chattering. In order to realize fast coordinated formation, the expected position trajectory of UAV is composed of the leader position information and the desired relative distance with UGV, based on local distributed theory, in the three-dimensional space. The tracking and formation controllers are proved to be stable by the Lyapunov theory and the simulation results demonstrate the effectiveness of proposed algorithms.  相似文献   

11.
In this paper, the problem of adaptive fuzzy fault-tolerant control is investigated for a class of switched uncertain pure-feedback nonlinear systems under arbitrary switching. The considered actuator failures are modeled as both lock-in-place and loss of effectiveness. By utilizing mean value theorem, the considered pure-feedback systems are transformed into a class of switched nonlinear strict-feedback systems. Under the framework of backstepping design technique and common Lyapunov function (CLF), an adaptive fuzzy fault-tolerant control (FTC) method with predefined performance bounds is developed. It is proved that under the proposed controller, all the signals of the close-loop systems are bounded and the state tracking error for each step remains within the prescribed performance bound (PPB) regardless of actuator faults and the system switchings. In addition, the tracking errors and magnitudes of control inputs can be reduced by adjusting the PPB parameters of errors in the first and last steps. The simulation results are provided to show the effectiveness of the proposed control scheme.  相似文献   

12.
In this paper, we study the consensus tracking control problem of a class of strict-feedback multi-agent systems (MASs) with uncertain nonlinear dynamics, input saturation, output and partial state constraints (PSCs) which are assumed to be time-varying. An adaptive distributed control scheme is proposed for consensus achievement via output feedback and event-triggered strategy in directed networks containing a spanning tree. To handle saturated control inputs, a linear form of the control input is adopted by transforming the saturation function. The radial basis function neural network (RBFNN) is applied to approximate the uncertain nonlinear dynamics. Since the system outputs are the only available data, a high-gain adaptive observer based on RBFNN is constructed to estimate the unmeasurable states. To ensure that the constraints of system outputs and partial states are never violated, a barrier Lyapunov function (BLF) with time-varying boundary function is constructed. Event-triggered control (ETC) strategy is applied to save communication resources. By using backstepping design method, the proposed distributed controller can guarantee the boundedness of all system signals, consensus tracking with a bounded error and avoidance of Zeno behavior. Finally, the correctness of the theoretical results is verified by computer simulation.  相似文献   

13.
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14.
This paper studies output feedback control of hydraulic actuators with modified continuous LuGre model based friction compensation and model uncertainty compensation. An output feedback adaptive robust controller is constructed which combines the adaptive control part and the robust control part seamlessly. The adaptive part is constructed to handle the parametric uncertainties existed in the model. The residuals coming from parameter adaption and the unmodeled dynamics are taken into consideration by the robust part. Since only the position signal is available, the velocity, pressure, and internal friction states are obtained by observation or estimation. The errors coming from observation and estimation are also dealt with the robust part. Furthermore, the convergence of the closed-loop controller–observer scheme is achieved by the Lyapunov method in the presence of parametric uncertainties only. Extensive comparative experiments performed on a hydraulic actuator demonstrate the effectiveness of the proposed controller–observer scheme.  相似文献   

15.
This paper investigates a novel strategy which can address the fault-tolerant control (FTC) problem for nonlinear strict-feedback systems containing actuator saturation, unknown external disturbances, and faults related to actuators and components. In such method, the unknown dynamics including faults and disturbances are approximated by resorting to Neural-Networks (NNs) technique. Meanwhile, a back-stepping technique is employed to build a fault-tolerant controller. It should be stressed that the main advantage of this strategy is that the NN weights are updated online based on gradient descent (GD) algorithm by minimizing the cost function with respect to NNs approximation error rather than regarding weights as adaptive parameters, which are designed according to Lyapunov theory. In addition, the convergence proof of NN weights and the stability proof of the proposed FTC method are given. Finally, simulation is performed to demonstrate the effectiveness of the proposed strategy in dealing with unknown external disturbances, actuator saturation and the faults related to the components and actuators, simultaneously.  相似文献   

16.
This paper studies the problem of composite control for a class of uncertain Markovian jump systems (MJSs) with partial known transition rates, multiple disturbances and actuator saturation. Compared with the existing results, a novel robust composite control scheme is put forward by virtue of adaptive neural network technique. For MJSs, the partial unknown information on transition rates and the actuator saturation influence the design of disturbance observer and the robust H∞ controller. Firstly, without taking account of external disturbances, the network reconstruction error and saturation, a novel robust adaptive control strategy is established to ensure that all the signals of the closed-loop system are asymptotically bounded in mean square. Secondly, the solvability condition for ensuring the robust H∞ performance is given by using a modified adaptive law, where the saturation is treated as a disturbance-like signal. Finally, the simulations for a numerical example and an application example are performed to validate the effectiveness of the proposed results.  相似文献   

17.
This paper studies the problem of observer based fast nonsingular terminal sliding mode control schemes for nonlinear non-affine systems with actuator faults, unknown states, and external disturbances. A hyperbolic tangent function based extended state observer is considered to estimate unknown states, which enhances robustness by estimating external disturbance. Then, Taylor series expansion is employed for the non-affine nonlinear system with actuator faults, which transforms it to an affine form system to simplify disturbance observer and controller design. A finite time disturbance observer is designed to address unknown compound disturbances, which includes external disturbances and system uncertainties. A fast nonsingular terminal sliding mode with exponential function sliding mode is proposed to address output tracking. Simulation results show the proposed scheme is effective.  相似文献   

18.
This article studies adaptive prescribed performance tracking control problem for a class of strict-feedback nonlinear systems with parametric uncertainties and actuator failures. Firstly, in order to compensate the multiple uncertainties and eliminate the influence of actuator failure, a new adaptive tracking controller based on first-order filter technology will be proposed, which simplifies the algorithm design process. Then, by introducing an asymmetric state transition function, the transient and steady performances of the output tracking error are both constrained such that the predetermined performance control goal is achieved. Moreover, to reduce the communication burden from the controller to the actuator, the event-triggered mechanism is designed, and there will be no Zeno phenomenon. Based on Lyapunov stability theory, it is strictly proved that output signal can track the reference signal and all the signals of the closed-loop system are bounded. Finally, a simulation example is performed and the results demonstrate effectiveness of the proposed strategy.  相似文献   

19.
In this paper, a robust actuator fault diagnosis scheme is investigated for satellite attitude control systems subject to model uncertainties, space disturbance torques and gyro drifts. A nonlinear unknown input observer is designed to detect the occurrence of any actuator fault. Subsequently, a bank of adaptive unknown input observers activated by the detection results are designed to isolate which actuator is faulty and then estimate of the fault parameter. Fault isolation is achieved based on the well known generalized observer strategy. The simulation on a closed-loop satellite control system with time-varying or constant actuator faults in the form of additive and multiplicative unknown dynamics demonstrates the effectiveness of the proposed robust fault diagnosis strategy.  相似文献   

20.
In this paper, a novel fast attitude adaptive fault-tolerant control (FTC) scheme based on adaptive neural network and command filter is presented for the hypersonic reentry vehicles (HRV) with complex uncertainties which contain parameter uncertainties, un-modeled dynamics, actuator faults, and external disturbances. To improve the performance of closed-loop FTC, command filter and neural network are introduced to reconstruct system nonlinearities that are related to complex uncertainties. Compared with the FTC scheme with only neural network, the FTC scheme with command filter and neural network has fewer controller design parameters so that the computational complexity is decreased and the control efficiency is improved, which is of great significance for HRV. Then, the adaptive backstepping fault-tolerant controller based on command filter and neural network is designed, which can solve the complexity explosion problem in the standard backstepping control and the small uncertainty problem in the backstepping control only containing command filter. Moreover, to improve the approximation accuracy of the neural network-based universal approximator, an adaptive update law of neural network weights is designed by using the convex optimization technique. It is proved that the presented FTC scheme can ensure that the closed-loop control system is stable and the tracking errors are convergent. Finally, simulation results are carried out to verify the superiority and effectiveness of the presented FTC scheme.  相似文献   

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